{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples and Exercises from Think Stats, 2nd Edition\n",
    "\n",
    "http://thinkstats2.com\n",
    "\n",
    "Copyright 2016 Allen B. Downey\n",
    "\n",
    "MIT License: https://opensource.org/licenses/MIT\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import brfss\n",
    "\n",
    "import thinkstats2\n",
    "import thinkplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scatter plots\n",
    "\n",
    "I'll start with the data from the BRFSS again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = brfss.ReadBrfss(nrows=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function selects a random subset of a `DataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SampleRows(df, nrows, replace=False):\n",
    "    indices = np.random.choice(df.index, nrows, replace=replace)\n",
    "    sample = df.loc[indices]\n",
    "    return sample"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'll extract the height in cm and the weight in kg of the respondents in the sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample = SampleRows(df, 5000)\n",
    "heights, weights = sample.htm3, sample.wtkg2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's a simple scatter plot with `alpha=1`, so each data point is fully saturated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.Scatter(heights, weights, alpha=1)\n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data fall in obvious columns because they were rounded off.  We can reduce this visual artifact by adding some random noice to the data.\n",
    "\n",
    "NOTE: The version of `Jitter` in the book uses noise with a uniform distribution.  Here I am using a normal distribution.  The normal distribution does a better job of blurring artifacts, but the uniform distribution might be more true to the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Jitter(values, jitter=0.5):\n",
    "    n = len(values)\n",
    "    return np.random.normal(0, jitter, n) + values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Heights were probably rounded off to the nearest inch, which is 2.8 cm, so I'll add random values from -1.4 to 1.4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "heights = Jitter(heights, 1.4)\n",
    "weights = Jitter(weights, 0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's what the jittered data look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.Scatter(heights, weights, alpha=1.0)\n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The columns are gone, but now we have a different problem: saturation.  Where there are many overlapping points, the plot is not as dark as it should be, which means that the outliers are darker than they should be, which gives the impression that the data are more scattered than they actually are.\n",
    "\n",
    "This is a surprisingly common problem, even in papers published in peer-reviewed journals.\n",
    "\n",
    "We can usually solve the saturation problem by adjusting `alpha` and the size of the markers, `s`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.Scatter(heights, weights, alpha=0.1, s=10)\n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's better.  This version of the figure shows the location and shape of the distribution most accurately.  There are still some apparent columns and rows where, most likely, people reported their height and weight using rounded values.  If that effect is important, this figure makes it apparent; if it is not important, we could use more aggressive jittering to minimize it. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An alternative to a scatter plot is something like a `HexBin` plot, which breaks the plane into bins, counts the number of respondents in each bin, and colors each bin in proportion to its count."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thinkplot.HexBin(heights, weights)\n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case the binned plot does a pretty good job of showing the location and shape of the distribution.  It obscures the row and column effects, which may or may not be a good thing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise:**  So far we have been working with a subset of only 5000 respondents.  When we include the entire dataset, making an effective scatterplot can be tricky.  As an exercise, experiment with `Scatter` and `HexBin` to make a plot that represents the entire dataset well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Solution\n",
    "\n",
    "# With smaller markers, I needed more aggressive jittering to\n",
    "# blur the measurement artifacts\n",
    "\n",
    "# With this dataset, using all of the rows might be more trouble\n",
    "# than it's worth.  Visualizing a subset of the data might be\n",
    "# more practical and more effective.\n",
    "\n",
    "heights = Jitter(df.htm3, 2.8)\n",
    "weights = Jitter(df.wtkg2, 1.0)\n",
    "\n",
    "thinkplot.Scatter(heights, weights, alpha=0.01, s=2)\n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting percentiles\n",
    "\n",
    "Sometimes a better way to get a sense of the relationship between variables is to divide the dataset into groups using one variable, and then plot percentiles of the other variable.\n",
    "\n",
    "First I'll drop any rows that are missing height or weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cleaned = df.dropna(subset=['htm3', 'wtkg2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then I'll divide the dataset into groups by height."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "bins = np.arange(135, 210, 5)\n",
    "indices = np.digitize(cleaned.htm3, bins)\n",
    "groups = cleaned.groupby(indices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the number of respondents in each group:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 305\n",
      "1 228\n",
      "2 477\n",
      "3 2162\n",
      "4 18759\n",
      "5 45761\n",
      "6 70610\n",
      "7 72138\n",
      "8 61725\n",
      "9 49938\n",
      "10 43555\n",
      "11 20077\n",
      "12 7784\n",
      "13 1777\n",
      "14 405\n",
      "15 131\n"
     ]
    }
   ],
   "source": [
    "for i, group in groups:\n",
    "    print(i, len(group))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can compute the CDF of weight within each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_heights = [group.htm3.mean() for i, group in groups]\n",
    "cdfs = [thinkstats2.Cdf(group.wtkg2) for i, group in groups]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And then extract the 25th, 50th, and 75th percentile from each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for percent in [75, 50, 25]:\n",
    "    weight_percentiles = [cdf.Percentile(percent) for cdf in cdfs]\n",
    "    label = '%dth' % percent\n",
    "    thinkplot.Plot(mean_heights, weight_percentiles, label=label)\n",
    "    \n",
    "thinkplot.Config(xlabel='Height (cm)',\n",
    "                 ylabel='Weight (kg)',\n",
    "                 axis=[140, 210, 20, 200],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise:** Yet another option is to divide the dataset into groups and then plot the CDF for each group.  As an exercise, divide the dataset into a smaller number of groups and plot the CDF for each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Solution\n",
    "\n",
    "bins = np.arange(140, 210, 10)\n",
    "indices = np.digitize(cleaned.htm3, bins)\n",
    "groups = cleaned.groupby(indices)\n",
    "cdfs = [thinkstats2.Cdf(group.wtkg2) for i, group in groups]\n",
    "\n",
    "thinkplot.PrePlot(len(cdfs))\n",
    "thinkplot.Cdfs(cdfs)\n",
    "thinkplot.Config(xlabel='Weight (kg)',\n",
    "                 ylabel='CDF',\n",
    "                 axis=[20, 200, 0, 1],\n",
    "                 legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function computes the covariance of two variables using NumPy's `dot` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Cov(xs, ys, meanx=None, meany=None):\n",
    "    xs = np.asarray(xs)\n",
    "    ys = np.asarray(ys)\n",
    "\n",
    "    if meanx is None:\n",
    "        meanx = np.mean(xs)\n",
    "    if meany is None:\n",
    "        meany = np.mean(ys)\n",
    "\n",
    "    cov = np.dot(xs-meanx, ys-meany) / len(xs)\n",
    "    return cov"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103.33290857697797"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights, weights = cleaned.htm3, cleaned.wtkg2\n",
    "Cov(heights, weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Covariance is useful for some calculations, but it doesn't mean much by itself.  The coefficient of correlation is a standardized version of covariance that is easier to interpret."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Corr(xs, ys):\n",
    "    xs = np.asarray(xs)\n",
    "    ys = np.asarray(ys)\n",
    "\n",
    "    meanx, varx = thinkstats2.MeanVar(xs)\n",
    "    meany, vary = thinkstats2.MeanVar(ys)\n",
    "\n",
    "    corr = Cov(xs, ys, meanx, meany) / np.sqrt(varx * vary)\n",
    "    return corr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The correlation of height and weight is about 0.51, which is a moderately strong correlation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5087364789734771"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Corr(heights, weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NumPy provides a function that computes correlations, too:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.50873648],\n",
       "       [0.50873648, 1.        ]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(heights, weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is a matrix with self-correlations on the diagonal (which are always 1), and cross-correlations on the off-diagonals (which are always symmetric)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pearson's correlation is not robust in the presence of outliers, and it tends to underestimate the strength of non-linear relationships.\n",
    "\n",
    "Spearman's correlation is more robust, and it can handle non-linear relationships as long as they are monotonic.  Here's a function that computes Spearman's correlation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def SpearmanCorr(xs, ys):\n",
    "    xranks = pd.Series(xs).rank()\n",
    "    yranks = pd.Series(ys).rank()\n",
    "    return Corr(xranks, yranks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For heights and weights, Spearman's correlation is a little higher:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5405846262320476"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SpearmanCorr(heights, weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Pandas `Series` provides a method that computes correlations, and it offers `spearman` as one of the options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SpearmanCorr(xs, ys):\n",
    "    xs = pd.Series(xs)\n",
    "    ys = pd.Series(ys)\n",
    "    return xs.corr(ys, method='spearman')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is the same as for the one we wrote."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5405846262320457"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SpearmanCorr(heights, weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An alternative to Spearman's correlation is to transform one or both of the variables in a way that makes the relationship closer to linear, and the compute Pearson's correlation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5317282605983465"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Corr(cleaned.htm3, np.log(cleaned.wtkg2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using data from the NSFG, make a scatter plot of birth weight versus mother’s age. Plot percentiles of birth weight versus mother’s age. Compute Pearson’s and Spearman’s correlations. How would you characterize the relationship between these variables?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import first\n",
    "\n",
    "live, firsts, others = first.MakeFrames()\n",
    "live = live.dropna(subset=['agepreg', 'totalwgt_lb'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Corr 0.06883397035410908\n",
      "SpearmanCorr 0.09461004109658226\n"
     ]
    }
   ],
   "source": [
    "# Solution\n",
    "\n",
    "ages = live.agepreg\n",
    "weights = live.totalwgt_lb\n",
    "print('Corr', Corr(ages, weights))\n",
    "print('SpearmanCorr', SpearmanCorr(ages, weights))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Solution\n",
    "\n",
    "def BinnedPercentiles(df):\n",
    "    \"\"\"Bin the data by age and plot percentiles of weight for each bin.\n",
    "\n",
    "    df: DataFrame\n",
    "    \"\"\"\n",
    "    bins = np.arange(10, 48, 3)\n",
    "    indices = np.digitize(df.agepreg, bins)\n",
    "    groups = df.groupby(indices)\n",
    "\n",
    "    ages = [group.agepreg.mean() for i, group in groups][1:-1]\n",
    "    cdfs = [thinkstats2.Cdf(group.totalwgt_lb) for i, group in groups][1:-1]\n",
    "\n",
    "    thinkplot.PrePlot(3)\n",
    "    for percent in [75, 50, 25]:\n",
    "        weights = [cdf.Percentile(percent) for cdf in cdfs]\n",
    "        label = '%dth' % percent\n",
    "        thinkplot.Plot(ages, weights, label=label)\n",
    "\n",
    "    thinkplot.Config(xlabel=\"Mother's age (years)\",\n",
    "                     ylabel='Birth weight (lbs)',\n",
    "                     xlim=[14, 45], legend=True)\n",
    "    \n",
    "BinnedPercentiles(live)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Solution\n",
    "\n",
    "def ScatterPlot(ages, weights, alpha=1.0, s=20):\n",
    "    \"\"\"Make a scatter plot and save it.\n",
    "\n",
    "    ages: sequence of float\n",
    "    weights: sequence of float\n",
    "    alpha: float\n",
    "    \"\"\"\n",
    "    thinkplot.Scatter(ages, weights, alpha=alpha)\n",
    "    thinkplot.Config(xlabel='Age (years)',\n",
    "                     ylabel='Birth weight (lbs)',\n",
    "                     xlim=[10, 45],\n",
    "                     ylim=[0, 15],\n",
    "                     legend=False)\n",
    "    \n",
    "ScatterPlot(ages, weights, alpha=0.05, s=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution\n",
    "\n",
    "# My conclusions:\n",
    "\n",
    "# 1) The scatterplot shows a weak relationship between the variables but\n",
    "#    it is hard to see clearly.\n",
    "\n",
    "# 2) The correlations support this.  Pearson's is around 0.07, Spearman's\n",
    "#    is around 0.09.  The difference between them suggests some influence\n",
    "#    of outliers or a non-linear relationsip.\n",
    "\n",
    "# 3) Plotting percentiles of weight versus age suggests that the\n",
    "#    relationship is non-linear.  Birth weight increases more quickly\n",
    "#    in the range of mother's age from 15 to 25.  After that, the effect\n",
    "#    is weaker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
